With the advent of image processing technology, physical documents, i.e., paper documents, are now stored digitally. The physical documents include various content types, such as text and image, which may be processed separately to generate a digital document. Such processing is generally performed to maintain a balance between quality of the digital document and a compression ratio. Lower compression ratio may ensure a higher quality but at the same time may substantially increase the file size, while a higher compression ratio may do the opposite. Therefore, typically, an image portion of the physical document may be processed to have a higher compression ratio, i.e., lower resolution, as compared to a text portion.
Often times, a text section of the physical document is highlighted to identify important content or content that may require attention. Owing to importance associated with such highlighted sections, such highlighted text sections are to be preserved, i.e., appropriately captured in a digital version of the physical document. However, available image processing techniques may erroneously identify a highlighted text section as an image. As a result, the highlighted text sections may not have appropriate image quality owing to high compression and may undergo lossy compression. Consequently, the highlighted text sections in the digital document may be illegible, blurred, or hazy, thereby defeating the purpose of highlighting such sections. Considering the highlighted sections are important for users, there is a need for efficient methods and systems to improve image quality for documents with highlighted sections/portions.